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Key message The GWAS and testing with Yr gene linked markers identified 109 loci including 40 novel loci for all-stage and adult plant stage resistance to stripe rust in 459 US contemporary hard winter wheat genotypes. Stripe rust is a destructive wheat disease, caused by Puccinia striiformis f. sp. tritici ( Pst ). To identify sources of stripe rust resistance in US contemporary hard winter wheat, a panel of 459 Great Plains wheat genotypes was evaluated at the seedling stage against five US Pst races and at the adult plant stage in field environments in Oklahoma, Kansas, and Washington. The results showed that 7–14% of the genotypes were resistant to Pst races at the seedling stage, whereas 32–78% of genotypes were resistant at the adult plant stage across field environments, indicating the presence of adult plant resistance. Sixteen genotypes displayed a broad spectrum of resistance to all five Pst races and across all field environments. The panel was further genotyped using 9858 single-nucleotide polymorphisms (SNPs) generated from multiplex restriction amplicon sequencing (MRASeq) and the functional DNA markers linked to the known stripe rust resistance ( Yr ) genes Yr5 , Yr15 , Yr17 , Yr18 , Yr29 , Yr36 , Yr40 , Yr46 , and QYr.tamu-2B . A genome-wide association study (GWAS) was performed using genotypic and phenotypic data, which identified 110 SNPs and the functional markers linked to Yr15 and Yr17 to be significantly associated with stripe rust response. In addition, Yr5 , Yr15 , Yr17 , Yr18 , Yr29 , and QYr.tamu-2B were detected by their functional DNA markers in the panel. This study identified 40 novel loci associated with stripe rust resistance in genomic regions not previously characterized by known Yr genes. These findings offer significant opportunities to diversify and enhance stripe rust resistance in hard winter wheat.

Plant breeding and disease management practices have increased the grain yield of hard winter wheat ( Triticum aestivum L.) adapted to the Great Plains of the United States during the last century. However, the effect of genetic gains for seed yield and the application of fungicide on the micronutrient and cadmium (Cd) concentration in wheat grains is still unclear. The objectives of this study were to evaluate the effects of fungicide application on the productivity and nutritional quality of wheat cultivars representing 80 years of plant breeding efforts. Field experiments were conducted over two crop years (2017 and 2018) with eighteen hard winter wheat genotypes released between 1933 and 2013 in the presence or absence of fungicide application. For each growing season, the treatments were arranged in a split-plot design with the fungicide levels (treated and untreated) as the whole plot treatments and the genotypes as split-plot treatments in triplicate. The effects on seed yield, grain protein concentration (GPC), micronutrients, phytic acid, and Cd in grains were measured. While the yield of wheat was found to increase at annualized rates of 26.5 and 13.0 kg ha -1 yr -1 in the presence and absence of fungicide ( P < 0.001), respectively, GPC (-190 and -180 mg kg -1 yr -1 , P < 0.001), Fe (-35.0 and -44.0 μg kg -1 yr -1 , P < 0.05), and Zn (-68.0 and -57.0 μg kg -1 yr -1 , P < 0.01) significantly decreased during the period studied. In contrast to the other mineral elements, grain Cd significantly increased over time (0.4 μg kg -1 yr -1 , P < 0.01) in the absence of fungicide. The results from this study are of great concern, as many mineral elements essential for human nutrition have decreased over time while the toxic heavy metal, Cd, has increased, indicating modern wheats are becoming a better vector of dietary Cd.

Leaf rust, caused by Puccinia triticina (Pt), is a serious constraint to wheat production. Developing resistant varieties is the best approach to managing this disease. Wheat leaf rust resistance (Lr) genes have been classified into either all‐stage resistance (ASR) or adult‐plant resistance (APR). The objectives of this study were to identify sources of leaf rust resistance in contemporary US hard winter wheat (HWW) and to dissect the genetic basis underlying leaf rust resistance in HWW. A panel of 732 elite HWW genotypes was evaluated for response to US Pt races at the seedling stage and at the adult plant stage in leaf rust nurseries in Oklahoma, Texas, and Kansas. Further, the panel was genotyped using multiplex restriction amplicon sequencing (MRA‐Seq) and DNA markers linked to the known ASR genes Lr18, Lr19, Lr21, Lr24, Lr37, and Lr42 and APR genes Lr34, Lr46, Lr67, Lr68, Lr77, and Lr78. Single nucleotide polymorphism (SNP) markers derived from MRA‐Seq, DNA markers linked to the known Lr genes, and the phenotypic data were used for genome‐wide association study (GWAS) to identify markers associated with leaf rust response. Gene postulation based on leaf rust reactions, DNA markers, and GWAS suggested the presence of Lr1, Lr2a, Lr10, Lr14a, Lr16, Lr18, Lr19, Lr21, Lr24, Lr26, Lr34, Lr37, Lr39, Lr42, Lr46, Lr68, Lr77, and Lr78 in the HWW panel. The GWAS identified 59 SNPs significantly associated with leaf rust response, of which 20 were likely associated with novel resistance loci and can be used to enhance wheat leaf rust resistance. Core Ideas Eight wheat genotypes carry effective broad‐spectrum all‐stage resistance. Thirteen known all‐stage leaf rust resistance genes were identified in hard winter wheat (HWW). The adult plant leaf rust resistance genes Lr34, Lr46, Lr68, Lr77, and Lr78 were found in HWW. The genome‐wide association study identified 59 single nucleotide polymorphisms significantly associated with leaf rust response. Twelve wheat genotypes carry a high number of alleles conferring resistance to leaf rust. Plain Language Summary Leaf rust is a serious constraint to wheat production. Developing resistant varieties is the best approach to manage this disease. Our objectives were to identify sources of leaf rust resistance in contemporary US hard winter wheat and to identify genomic regions associated with leaf rust resistance. A collection of 732 advanced wheat lines was evaluated for response to leaf rust in multiple locations in the United States. Further, the wheat collection was genotyped using DNA markers. Leaf rust reactions and DNA markers were used to identify genomic regions associated with leaf rust resistance using a statistical approach called genome‐wide association study (GWAS). Reactions to leaf rust, DNA markers, and GWAS identified 18 previously known leaf rust resistance genes in this wheat collection. Furthermore, the GWAS identified an additional 59 genomic regions significantly associated with leaf rust response, of which 20 were likely novel and could be used to enhance leaf rust resistance in wheat.

Soybean cyst nematode ( Ichinohe) (SCN) is the most destructive pest affecting soybeans [ (L.) Merr.] in the U.S. To date, only two major SCN resistance alleles, and , identified in PI 88788 ( ) and Peking ( ), residing on chromosomes (Chr) 18 and 8, respectively, have been widely used to develop SCN resistant cultivars in the U.S. Thus, some SCN populations have evolved to overcome the PI 88788 and Peking derived resistance, making it a priority for breeders to identify new alleles and sources of SCN resistance. Toward that end, 461 soybean accessions from various origins were screened using a greenhouse SCN bioassay and genotyped with Illumina SoySNP50K iSelect BeadChips and three KASP SNP markers developed at the and loci to perform a genome-wide association study (GWAS) and a haplotype analysis at the and loci. In total, 35,820 SNPs were used for GWAS, which identified 12 SNPs at four genomic regions on Chrs 7, 8, 10, and 18 that were significantly associated with SCN resistance ( < 0.001). Of those, three SNPs were located at and , and 24 predicted genes were found near the significant SNPs on Chrs 7 and 10. KASP SNP genotyping results of the 462 accessions at the and loci identified 30 that carried PI 88788-type resistance, 50 that carried Peking-type resistance, and 58 that carried neither the Peking-type nor the PI 88788-type resistance alleles, indicating they may possess novel SCN resistance alleles. By using two subsets of SNPs near the and loci obtained from SoySNP iSelect BeadChips, a haplotype analysis of 461 accessions grouped those 58 accessions differently from the accessions carrying Peking or PI 88788 derived resistance, thereby validating the genotyping results at and . The significant SNPs, candidate genes, and newly characterized SCN resistant accessions will be beneficial for the development of DNA markers to be used for marker-assisted breeding and developing soybean cultivars carrying novel sources of SCN resistance.

Hexaploid‐derived resistance genes exhibit complex inheritance and expression patterns in tetraploid backgrounds. This study aimed to characterize the inheritance patterns and genomic compatibilities of hexaploid‐derived Fusarium head blight (FHB) resistance genes in tetraploid durum wheat (Triticum durum Desf.). Evaluation of FHB resistance for F1 hybrids of hexaploid ‘Sumai 3’ crossed with tetraploid and hexaploid wheats indicated that Sumai 3‐derived FHB resistance genes exhibit a dominant phenotypic effect seen only in hexaploid hybrids. Alternately, the hexaploid‐derived FHB resistance genes from PI 277012 exhibited complete dominance in the crosses with both tetraploid and hexaploid wheat. FHB evaluation of the F1 hybrids of Sumai 3 and PI 277012 crossed with ‘Langdon’ (LDN)–‘Chinese Spring’ D‐genome substitution lines suggested that chromosomes 2B, 3B, 4B, 5B, 6B, 3A, 4A, 6A, and 7A contain genes that suppress expression of the Sumai 3‐derived FHB resistance, whereas chromosomes 4A, 6A, and 6B contain genes required for expression of PI 277012‐derived FHB resistance. A wide range of segregation for FHB severity (10–90%) was observed in the F2 generation of Sumai 3 crossed with durum cultivars LDN and ‘Divide’, but the distribution of F3 families derived from the most resistant F2 segregants was skewed towards susceptibility. Similar segregation trends were observed in the crosses of PI 277012 with other durum wheats, whereby FHB resistance became slightly diluted over successive generations. These results suggest tetraploid durum wheat contains the unique alleles at multiple gene loci on different chromosomes that positively and/or negatively regulate the expression of hexaploid‐derived FHB resistance genes, which complicate efforts to deploy these genes in durum breeding programs. Core Ideas Durum contains genes that enhance or suppress hexaploid‐derived FHB resistance. The hexaploid‐derived FHB resistance genes were inherited differently in durum. Genomic compatibility for FHB resistance was assessed by D genome substitutions. Sumai 3‐derived FHB resistance was suppressed by loci on nine durum chromosomes. Three durum chromosomes contain loci needed for PI 277012‐derived FHB resistance.

Key messageFour soybean storage protein subunit QTLs were mapped using bulked segregant analysis and an F2 population, which were validated with an F5 RIL population.The storage protein globulins β-conglycinin (7S subunit) and glycinin (11S subunits) can affect the quantity and quality of proteins found in soybean seeds and account for more than 70% of the total soybean protein. Manipulating the storage protein subunits to enhance soymeal nutrition and for desirable tofu manufacturing characteristics are two end-use quality goals in soybean breeding programs. To aid in developing soybean cultivars with desired seed composition, an F2 mapping population (n = 448) and an F5 RIL population (n = 180) were developed by crossing high protein cultivar ‘Harovinton’ with the breeding line SQ97-0263_3-1a, which lacks the 7S α′, 11S A1, 11S A2, 11S A3 and 11S A4 subunits. The storage protein composition of each individual in the F2 and F5 populations were profiled using SDS-PAGE. Based on the presence/absence of the subunits, genomic DNA bulks were formed among the F2 plants to identify genomic regions controlling the 7S α′ and 11S protein subunits. By utilizing polymorphic SNPs between the bulks characterized with Illumina SoySNP50K iSelect BeadChips at targeted genomic regions, KASP assays were designed and used to map QTLs causing the loss of the subunits. Soybean storage protein QTLs were identified on Chromosome 3 (11S A1), Chromosome 10 (7S α′ and 11S A4), and Chromosome 13 (11S A3), which were also validated in the F5 RIL population. The results of this research could allow for the deployment of marker-assisted selection for desired storage protein subunits by screening breeding populations using the SNPs linked with the subunits of interest.

Core Ideas Techniques included near‐isogenic lines, 90k single nucleotide polymorphism (SNP) chip, and genomic in situ hybridization. Single nucleotide polymorphism genotyping identified a 5DS–5BS translocation break point in durum wheat. Genomic in situ hybridization corroborated the presence of a 5DS–5BS terminal translocation. The durum wheat (Triticum turgidum ssp. durum (Desf.) Husn.) cultivar Soft Svevo with a soft kernel texture was developed through a Ph1b‐mediated homoeologous 5DS–5BS chromosomal translocation. The soft kernel trait (Hardness locus) derived from chromosome 5D of the common wheat (Triticum aestivum L.) cultivar Chinese Spring. Soft Svevo was used as the donor parent to create near‐isogenic soft durum germplasm. The size of the translocation, its estimated breakpoint, and the amount of chromosome 5BS translocated, if any, remain unknown. Four near‐isogenic pairs of hard and soft kernel durum genotypes, in addition to Soft Svevo and the Chinese Spring deletion line 5DS‐2, which lacks a distal 22% terminal segment of chromosome 5DS, were genotyped using Illumina's 90k wheat single nucleotide polymorphism array. Single nucleotide polymorphism results were processed in GenomeStudio and 164 polymorphic markers were identified between the near‐isogenic lines (NILs). Subsequent BLASTn results for two subsets of markers corresponding to the distal ends of chromosomes 5DS and 5BS indicated that the translocation event was nearly reciprocal, as a ∼24.36‐Mbp segment of chromosome 5DS was gained, whereas a ∼20.01‐Mbp segment of chromosome 5BS was lost. Genomic in situ hybridization images of the soft durum NILs agreed with these estimates and confirmed the absence of additional terminal or interstitial translocations. Soft durum represents the potential of a new wheat market class and these findings will assist durum wheat breeders in the development of new soft durum germplasm.

Leaf rust, caused by Puccinia triticina (Pt), is a serious constraint to wheat production. Developing resistant varieties is the best approach to managing this disease. Wheat leaf rust resistance (Lr) genes have been classified into either all-stage resistance (ASR) or adult-plant resistance (APR). The objectives of this study were to identify sources of leaf rust resistance in contemporary U.S. hard winter wheat (HWW) and to dissect the genetic basis underlying leaf rust resistance in HWW. A panel of 732 elite HWW genotypes was evaluated for response to U.S. Pt races at the seedling stage and at the adult plant stage in leaf rust nurseries in Oklahoma, Texas, and Kansas. Further, the panel was genotyped using Multiplex Restriction Amplicon Sequencing (MRA-Seq) and DNA markers linked to the known ASR genes Lr18, Lr19, Lr21, Lr24, Lr37, and Lr42 and APR genes Lr34, Lr46, Lr67, Lr68, Lr77, and Lr78. Single nucleotide polymorphism (SNP) markers derived from MRA-Seq, DNA markers linked to the known Lr genes, and the phenotypic data were used for genome-wide association study (GWAS) to identify markers associated with leaf rust response. Gene postulation based on leaf rust reactions, DNA markers, and GWAS suggested the presence of Lr1, Lr2a, Lr10, Lr14a, Lr16, Lr18, Lr19, Lr21, Lr24, Lr26, Lr34, Lr37, Lr39, Lr42, Lr46, Lr68, Lr77, and Lr78 in the HWW panel. The GWAS identified 59 SNPs significantly associated with leaf rust response, of which 20 were likely associated with novel resistance loci and can be used to enhance wheat leaf rust resistance.

Spatially explicit estimates of species abundance and distribution are increasingly needed to support conservation planning and management across multiple spatial scales. We present a generalized modeling framework that bridges the gap between local studies and regional to national planning by compiling and harmonizing diverse datasets to predict avian abundance at fine resolution and broad extent. We applied detectability offsets to integrate point‐count data from over 250,000 locations across subarctic Canada. Data were subsampled by two time periods and 16 geographic regions, and we used boosted regression trees to model the density of 143 boreal landbird species as a function of climate, vegetation composition (local [250 m] and landscape [~1.5 km]), land cover, and topography. Bootstrapped regional predictions were combined to generate density maps, region‐ and habitat‐specific estimates, and Canada‐wide population totals. We estimated ~3.56 billion breeding males (7.13 billion individuals), with most occurring in boreal and hemi‐boreal regions. Forest generalists accounted for nearly half the total (1.57 billion males), followed by boreal specialists (1.05 billion), habitat generalists (350 million), and species associated with eastern forests (274 million), grasslands (124 million), western forests (74.7 million), wetlands (63.5 million), and Arctic tundra (17.7 million). Introduced species totaled 48.9 million breeding males. Across species, landscape‐level vegetation composition explained most variation in abundance, indicating that climate effects are primarily indirect, operating through vegetation. Landscape‐scale variables were critical to capturing this variation. Model classification accuracy was highest for forest‐ and grassland‐associated species (lowest for mountain and urban species), and for the families Regulidae and Phasianidae (lowest for Bombycillidae and Paridae). This work provides a standardized, updatable, and reproducible workflow for generating spatially explicit bird abundance estimates. These products can be revised as new data become available and used to support ongoing conservation and land‐use decisions. Résumé Des estimations spatiales de l'abondance et de la distribution des espèces sont de plus en plus nécessaires pour appuyer la planification de la conservation et les décisions de gestion à différentes échelles spatiales. Nous présentons un cadre de modélisation généralisé qui comble l'écart entre les études locales et les besoins d'aménagement régionaux à nationaux, en compilant et en harmonisant des données provenant de nombreuses sources afin de prédire l'abondance d'oiseaux à une résolution fine et à grande échelle. Nous avons appliqué des variables de compensation de détectabilité pour intégrer des données de points d'écoute provenant de plus de 250,000 lieux d'échantillonnage dans l'ensemble du Canada subarctique. Les données ont été sous‐échantillonnées selon deux périodes de temps et seize régions géographiques, et nous avons utilisé des arbres de régression optimisés pour modéliser la densité de 143 espèces d'oiseaux terrestres en zone boréale en fonction de covariables environnementales représentant le climat, composition végétale au niveau local (250 m) et du paysage (~1.5 km), la couverture terrestre et la topographie. Les prédictions régionales issues des modèles par bootstrap ont été combinées pour produire des cartes de densité, des estimations spécifiques à l'habitat et à la région, ainsi que des estimations à l'échelle du Canada. Nous avons estimé environ 3.56 milliards de mâles reproducteurs (7.13 milliards d'individus), la majorité se trouvant dans les régions boréales et hémiboréales. Les espèces forestières généralistes représentaient près de la moitié de cette estimation (1.57 milliard), suivies des spécialistes de la forêt boréale (1.05 milliard), des espèces généralistes (350 millions) et des espèces associées aux forêts de l'est (274 millions), aux prairies (124 millions), aux forêts de l'ouest (74.7 millions), aux milieux humides (63.5 millions) et à la toundra arctique (17.7 millions). Les espèces introduites représentaient 48.9 millions de mâles reproducteurs. Pour la majorité des espèces, la composition de la végétation à l'échelle du paysage expliquait la plus grande part de la variation de l'abondance, ce qui suggère un effet climatique principalement indirect, agissant par l'intermédiaire de la végétation. Les variables à l'échelle du paysage étaient essentielles pour capturer cette variation. L'exactitude de la classification était la plus élevée pour les espèces associées aux forêts et aux prairies (la plus faible pour les espèces de montagne et urbaines) et pour les familles des Regulidae et des Phasianidae (la plus faible pour les Bombycillidae et les Paridae). Ce travail fournit une structure de modélisation standardisée, modifiable et reproductible permettant de générer des estimations spatiales de l'abondance d'oiseaux. Ces produits peuvent être mis à jour à mesure que de nouvelles données deviennent disponibles et utilisés pour soutenir la conservation et la planification de l'aménagement du territoire.

Chronic heart failure is associated with high mortality and morbidity. Raised resting heart rate is a risk factor for adverse outcomes. We aimed to assess the effect of heart-rate reduction by the selective sinus-node inhibitor ivabradine on outcomes in heart failure. Patients were eligible for participation in this randomised, double-blind, placebo-controlled, parallel-group study if they had symptomatic heart failure and a left-ventricular ejection fraction of 35% or lower, were in sinus rhythm with heart rate 70 beats per min or higher, had been admitted to hospital for heart failure within the previous year, and were on stable background treatment including a β blocker if tolerated. Patients were randomly assigned by computer-generated allocation schedule to ivabradine titrated to a maximum of 7·5 mg twice daily or matching placebo. Patients and investigators were masked to treatment allocation. The primary endpoint was the composite of cardiovascular death or hospital admission for worsening heart failure. Analysis was by intention to treat. This trial is registered, number ISRCTN70429960. 6558 patients were randomly assigned to treatment groups (3268 ivabradine, 3290 placebo). Data were available for analysis for 3241 patients in the ivabradine group and 3264 patients allocated placebo. Median follow-up was 22·9 (IQR 18–28) months. 793 (24%) patients in the ivabradine group and 937 (29%) of those taking placebo had a primary endpoint event (HR 0·82, 95% CI 0·75–0·90, p<0·0001). The effects were driven mainly by hospital admissions for worsening heart failure (672 [21%] placebo vs 514 [16%] ivabradine; HR 0·74, 0·66–0·83; p<0·0001) and deaths due to heart failure (151 [5%] vs 113 [3%]; HR 0·74, 0·58–0·94, p=0·014). Fewer serious adverse events occurred in the ivabradine group (3388 events) than in the placebo group (3847; p=0·025). 150 (5%) of ivabradine patients had symptomatic bradycardia compared with 32 (1%) of the placebo group (p<0·0001). Visual side-effects (phosphenes) were reported by 89 (3%) of patients on ivabradine and 17 (1%) on placebo (p<0·0001). Our results support the importance of heart-rate reduction with ivabradine for improvement of clinical outcomes in heart failure and confirm the important role of heart rate in the pathophysiology of this disorder. Servier, France.